Using chaos to improve generalization in smart NN control design

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

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Detail(s)

Original languageEnglish
Pages (from-to)301-306
Journal / PublicationIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume15
Issue number1
Publication statusPublished - 2002

Conference

Title15th World Congress of the International Federation of Automatic Control (IFAC World Congress 2002)
PlaceSpain
CityBarcelona
Period21 - 26 July 2002

Abstract

In this paper, a smart NN control scheme is proposed. This scheme is designed such that the current control action can utilize the knowledge that the NN learned from the past control process. A chaotic signal is employed as the reference signal to improve the generalization ability of the NN in the training phase of the scheme, where the complex chaotic signal offers much more information for NN learning thereby significantly improving the efficiency of the NN generalization. Compared with most of the adaptive neural controllers, the smart neural controller (in the operational phase) is a static and low-order controller, and thus needs much less computational resources, and is more feasible in practical implementation. Simulation studies are included to demonstrate the effectiveness of the new control scheme.

Research Area(s)

  • Chaos, Generalization, Neural network (NN), Smart NN control

Citation Format(s)

Using chaos to improve generalization in smart NN control design. / Wang, Cong; Chen, Guanrong; Ge, Shuzhi S.

In: IFAC Proceedings Volumes (IFAC-PapersOnline), Vol. 15, No. 1, 2002, p. 301-306.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review